29 SNAT2 AS A NOVEL TARGETABLE VULNERABILITY IN RECURRENT GLIOBLASTOMA
Bibliographic record
Abstract
Abstract Glioblastoma (GBM) is the most fatal primary brain tumour. Standard-of-care consists of surgical resection followed by chemo-radiotherapy, but the tumour almost always recurs. There are currently no effective treatments at recurrence, and this contributes to why patients with GBM have a median survival of only 13.5 months. GBM recurrence is thought to arise due to treatment-resistant GBM stem-like cells (GSCs), rendering them an important population to consider when developing effective therapeutics. A recent genome-wide CRISPR-Cas9 knockout (KO) screen in primary and recurrent GBM GSCs identified sodium-coupled neutral amino acid transporter 2 (SNAT2) as a vulnerability in recurrent GBM (rGBM), but not primary GBM (pGBM). SNAT2 transports neutral amino acids such as glycine, alanine and glutamine and is implicated in other cancers but its role in GBM remains unexplored. Here, we conducted comprehensive metabolomics comparing patient-matched pGBM and rGBM GSCs and explored the changes in the metabolome ofSNAT2 KO rGBM GSCs. We found that the metabolome of SNAT2 KO rGBM GSCs shares similarities with the metabolome of pGBM GSCs, which are notably less aggressive. Functionally, we found that SNAT2 KO in rGBM GSCs decreases proliferation, sphere formation and invasion capacity and increases the presence of reactive oxygen species in vitro. In vivo, SNAT2 KO decreases tumour burden and extends the survival of our patient-derived xenograft model of rGBM GSCs. This study bolsters SNAT2 as a novel targetable vulnerability in rGBM and provides proof of concept for future therapeutic development aiming to provide patients with additional treatment options.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".